What problem does it solve? Writing an effective skill is hard to get right on the first try, and there is no built-in way to know whether a skill actually improves Claude's output or triggers when it should. This Skill provides a structured draft-test-review-improve loop with quantitative benchmarking so skill quality is measured rather than guessed. ## Core Features & Use Cases - Guided skill authoring: Interview-driven capture of intent, trigger contexts, and output formats, then generation of a well-structured SKILL.md following progressive disclosure and writing-style best practices. - Evaluation harness: Runs test prompts with and without the skill in parallel subagents, grades outputs against assertions, and aggregates pass rates, timing, and token usage into benchmark.json with mean and standard deviation. - Description optimization: Generates realistic should-trigger and should-not-trigger queries, then runs an automated train/test optimization loop to improve the skill's triggering accuracy. - Use Case: You want a skill that formats weekly sales reports. This Skill helps you draft it, runs three realistic test prompts with and without the skill, opens a browser viewer for side-by-side review, and iterates until the outputs pass your assertions. ## Quick Start Help me create a new skill that converts meeting transcripts into structured action-item lists, then test it with a few realistic prompts.